Hypothesis Development
A hypothesis is a testable prediction or proposed explanation for a phenomenon, expressed as a relationship between variables. Hypothesis development is the process of formulating null hypotheses (H₀, asserting no effect or relationship) and alternative hypotheses (H₁, asserting an effect or relationship) before data collection. This framework emerged from frequentist statistical theory developed by Ronald Fisher in the 1920s and refined by Neyman and Pearson in the 1930s. Hypotheses are essential in quantitative research because they translate research questions into statements that can be tested using statistical inference.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Fisher, R. A. (1925). Statistical Methods for Research Workers. Oliver & Boyd. · URL
- Neyman, J., & Pearson, E. S. (1933). On the problem of the most efficient tests of statistical hypotheses. Philosophical Transactions of the Royal Society, 231(A), 289–337. · DOI 10.1098/rsta.1933.0009
- Kerlinger, F. N. (1964). Foundations of Behavioral Research. Holt, Rinehart and Winston. · URL
Curated claims
Claims persisted in the evidence ledger, each with its own assessment.
This view does not invent a claim assessment when the ledger has none.
Related methods
Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.